Lifting Line Framework for Optimization of Rotary Wing Systems

2022 ◽  
Author(s):  
Yogi Patel ◽  
Phillip J. Ansell
Keyword(s):  
Author(s):  
Iftekhar A. Riyad ◽  
Uttam K. Chakravarty

Rotary wing aircrafts in any flight conditions suffer from excessive vibration which makes the passengers feel uncomfortable and causes fatigue failure in the structure. The main sources of vibration are the rotor harmonic airloads which originate primarily from the rapid variation of flow around the blade due to the vortex wake. Unlike fixed wing aircrafts, helicopter wake consists of helical vortex sheets trailed behind each blade and remains under the rotor disk which induces vertical downwash velocities at chordwise and spanwise stations of the blade. In this study, a mathematical model is developed for rotor blades to compute the harmonic loads induced velocity at rotor blades for two flight conditions-vertical takeoff and landing, and forward flight. This method is useful for the performance analysis of rotor blade and selection of airfoils for the blade. The sectional lift, drag, and pitching moment are computed at a radial blade station for both flight conditions. The numerical integration of Biot-Savart relation are done for all the trailing and shed vortices to calculate the downwash through the rotor disc. The airloads are calculated using the relation between harmonic and inflow coefficients. The lift at a particular radial station is computed considering trailing and shed vortices and summing over each blade. Lifting-surface and lifting-line theories are applied to near wake and far wake, respectively, to calculate the downwash and inflow through the rotor disc. The results for lift are compared to the experimental flight-test data.


2020 ◽  
Vol 71 (7) ◽  
pp. 828-839
Author(s):  
Thinh Hoang Dinh ◽  
Hieu Le Thi Hong

Autonomous landing of rotary wing type unmanned aerial vehicles is a challenging problem and key to autonomous aerial fleet operation. We propose a method for localizing the UAV around the helipad, that is to estimate the relative position of the helipad with respect to the UAV. This data is highly desirable to design controllers that have robust and consistent control characteristics and can find applications in search – rescue operations. AI-based neural network is set up for helipad detection, followed by optimization by the localization algorithm. The performance of this approach is compared against fiducial marker approach, demonstrating good consensus between two estimations


Author(s):  
Jose Rodolfo Chreim ◽  
Marcos Pimenta ◽  
Joao Lucas D. Dantas ◽  
Gustavo Assi

1998 ◽  
Author(s):  
Clarence E. Rash ◽  
William E. McLean ◽  
John C. Mora ◽  
Melissa H. Ledford ◽  
Ben T. Mozo

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